A SHA-256 Hybrid-Redundancy Hardware Architecture for Detecting and Correcting Errors

In emergent technologies, data integrity is critical for message-passing communications, where security measures and validations must be considered to prevent the entrance of invalid data, detect errors in transmissions, and prevent data loss. The SHA-256 algorithm is used to tackle these requirements. Current hardware architecture works present issues regarding real-time balance among processing, efficiency and cost, because some of them introduce significant critical paths. Besides, the SHA-256 algorithm itself considers no verification mechanisms for internal calculations and failure prevention. Hardware implementations can be affected by diverse problems, ranging from physical phenomena to interference or faults inherent to data spectra. Previous works have mainly addressed this problem through three kinds of redundancy: information, hardware, or time. To the best of our knowledge, pipelining has not been previously used to perform different hash calculations with a redundancy topic. Therefore, in this work, we present a novel hybrid architecture, implemented on a 3-stage pipeline structure, which is traditionally used to improve performance by simultaneously processing several blocks; instead, we propose using a pipeline technique for implementing hardware and time redundancies, analyzing hardware resources and performance to balance the critical path. We have improved performance at a certain clock speed, defining a data flow transformation in several sequential phases. Our architecture reported a throughput of 441.72 Mbps and 2255 LUTs, and presented an efficiency of 195.8 Kbps/LUT.

[1]  J. Yonnet,et al.  Noise analysis of a high sensitivity GMI sensor based on a Field-Programmable-Gate-Array , 2021 .

[2]  Atin Mukherjee,et al.  A New Power-Gated Hybrid Defect Tolerant Approach Based on Modular Redundancy , 2021, 2021 Asian Conference on Innovation in Technology (ASIANCON).

[3]  Ignacio Algredo-Badillo,et al.  Hybrid Pipeline Hardware Architecture Based on Error Detection and Correction for AES , 2021, Sensors.

[4]  Xinghua Liu,et al.  Research on Hybrid Redundancy Voting Algorithm Based on Fuzzy Theory , 2021, Journal of Physics: Conference Series.

[5]  V. T. Nguyen,et al.  Immunity Characterization of FPGA I/Os for Fault-Tolerant Circuit Designs against EMI , 2019, Advances in Electrical and Computer Engineering.

[6]  Naraig Manjikian,et al.  A study of maximum frequency in FPGA chips using mesh and toroid circuit topologies , 2017, 2017 IEEE 30th Canadian Conference on Electrical and Computer Engineering (CCECE).

[7]  Fatma Kahri,et al.  An efficient fault detection scheme for the secure hash algorithm SHA-512 , 2017, 2017 International Conference on Green Energy Conversion Systems (GECS).

[8]  Rubén Darío Nieto,et al.  FPGA implementation of the AES-128 algorithm in non-feedback modes of operation , 2016 .

[9]  George Athanasiou,et al.  Design and implementation of totally-self checking SHA-1 and SHA-256 hash functions' architectures , 2016, Microprocess. Microsystems.

[10]  Fabian Vargas,et al.  Analysis of FPGA SEU sensitivity to combined effects of conducted EMI and TID , 2016, 2016 Asia-Pacific International Symposium on Electromagnetic Compatibility (APEMC).

[11]  George Athanasiou,et al.  Hardware implementation of the Totally Self-Checking SHA-256 hash core , 2015, IEEE EUROCON 2015 - International Conference on Computer as a Tool (EUROCON).

[12]  Yong-Bin Kim,et al.  Asynchronous Advanced Encryption Standard Hardware with Random Noise Injection for Improved Side-Channel Attack Resistance , 2014, J. Electr. Comput. Eng..

[13]  Rommel García,et al.  A compact FPGA-based processor for the Secure Hash Algorithm SHA-256 , 2014, Comput. Electr. Eng..

[14]  Ignacio Algredo-Badillo,et al.  FPGA-based implementation alternatives for the inner loop of the Secure Hash Algorithm SHA-256 , 2013, Microprocess. Microsystems.

[15]  S. Ravi,et al.  A survey on fault tolerance in FPGAs , 2013, 2013 7th International Conference on Intelligent Systems and Control (ISCO).

[16]  Elena Dubrova,et al.  Fault-Tolerant Design , 2013 .

[17]  Arvind Rajawat,et al.  A Review of FPGA-based design methodologies for efficient hardware Area estimation , 2013 .

[18]  Warren Shum,et al.  Glitch Reduction and CAD Algorithm Noise in FPGAs , 2011 .

[19]  Arash Reyhani-Masoleh,et al.  A Fault Detection Scheme for the FPGA Implementation of SHA-1 and SHA-512 Round Computations , 2011, J. Electron. Test..

[20]  Shadi Aljawarneh,et al.  A Semantic Data Validation Service for Web Applications , 2010, J. Theor. Appl. Electron. Commer. Res..

[21]  Shuja Ahmad Abbasi,et al.  A review of FPGA-based design methodology and optimization techniques for efficient hardware realization of computation intensive algorithms , 2009, 2009 International Multimedia, Signal Processing and Communication Technologies.

[22]  Russell Tessier,et al.  FPGA Architecture: Survey and Challenges , 2008, Found. Trends Electron. Des. Autom..

[23]  Imtiaz Ahmad,et al.  Analysis and Detection Of Errors In Implementation Of SHA-512 Algorithms On FPGAs , 2007, Comput. J..

[24]  R. C. Cofer,et al.  Rapid System Prototyping with FPGAs: Accelerating the Design Process , 2005 .

[25]  A. Singh,et al.  Fault-tolerant systems , 1990, Computer.